Radiology

Evaluation of deep learning reconstruction on diffusion-weighted imaging quality and apparent diffusion coefficient using an ice-water phantom.

This study assessed the influence of deep learning reconstruction (DLR) on the quality of diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) using an ice-water phantom. An ice-water phantom with known diffusion properties (true ADC = 1.1 × 10 mm/s at 0 °C) was imaged at various b-values (0, 1000, 2000, and 4000 s/mm) using a 3 T magnetic resonance imaging scanner with slice t...

A Robust Machine Learning Model for Diabetic Retinopathy Classification.

Ensemble learning is a process that belongs to the artificial intelligence (AI) field. It helps to choose a robust machine learning (ML) model, usually used for data classification. AI has a large connection with image processing and feature classification, and it can also be successfully applied to analyzing fundus eye images. Diabetic retinopathy (DR) is a disease that can cause vision loss and ...

Discrimination of benign and malignant breast lesions on dynamic contrast-enhanced magnetic resonance imaging using deep learning.

PURPOSE: To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast...

Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping.

BACKGROUND: Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensit...

Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study.

OBJECTIVES: We aimed to assess undergraduate medical students' knowledge, attitude, and perception regarding artificial intelligence (AI) in medicine.

Machine learning based on magnetic resonance imaging and clinical parameters helps predict mesenchymal-epithelial transition factor expression in oral tongue squamous cell carcinoma: a pilot study.

OBJECTIVES: This study aimed to develop machine learning models to predict phosphorylated mesenchymal-epithelial transition factor (p-MET) expression ...

The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions.

The rapid advancements in artificial intelligence (AI), including machine learning (ML), and deep learning (DL) have ushered in a new era of technolog...

Early prediction of distant metastasis in patients with uterine cervical cancer treated with definitive chemoradiotherapy by deep learning using pretreatment [ 18 F]fluorodeoxyglucose positron emission tomography/computed tomography.

OBJECTIVES: A deep learning (DL) model using image data from pretreatment [ 18 F]fluorodeoxyglucose ([ 18 F] FDG)-PET or computed tomography (CT) augm...

Exploring the impact of super-resolution deep learning on MR angiography image quality.

PURPOSE: The aim of this study is to assess the effect of super-resolution deep learning-based reconstruction (SR-DLR), which uses k-space properties,...

Analysis of the Screw Accuracy and Postoperative Efficacy of Screw Placement in Single Position and Bipedal Position in Robot-Assisted Oblique Lumbar Interbody Fusion: Preliminary Results of Mazor X Stealth Usage.

OBJECTIVE: Traditional manual OLIF combined with pedicle screw implantation has many problems of manual percutaneous screw implantation, such as high ...

Exploring the infiltrative and degradative ability of Fusarium oxysporum on polyethylene terephthalate (PET) using correlative microscopy and deep learning.

Managing the worldwide steady increase in the production of plastic while mitigating the Earth's global pollution is one of the greatest challenges no...

A novel deep learning model for a computed tomography diagnosis of coronary plaque erosion.

Patients with acute coronary syndromes caused by plaque erosion might be managed conservatively without stenting. Currently, the diagnosis of plaque e...

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.

OBJECTIVES: In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical l...

Detection and classification of brain tumor using hybrid deep learning models.

Accurately classifying brain tumor types is critical for timely diagnosis and potentially saving lives. Magnetic Resonance Imaging (MRI) is a widely u...

Cognitive workload estimation using physiological measures: a review.

Estimating cognitive workload levels is an emerging research topic in the cognitive neuroscience domain, as participants' performance is highly influe...

Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine.

Personalized medicine transforms healthcare by adapting interventions to individuals' unique genetic, molecular, and clinical profiles. To maximize di...

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging t...

Sonographically-navigated frozen shoulder release (S-FSR): A modified technique for sonographically-navigated, in-office hydrodilatation of adhesive capsulitis.

We describe a new technique for hydrodilatation of the frozen shoulder, which we coined 'Sonographically-Navigated Frozen Shoulder Release (S-FSR)' or...

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from pot...

Artificial intelligence-enabled ophthalmoscopy for papilledema: a systematic review protocol.

Papilledema is a pathology delineated by the swelling of the optic disc secondary to raised intracranial pressure (ICP). Diagnosis by ophthalmoscopy c...